Automated assessment of adult periodontal disease by computer processing of bitewing radiographs has significant potential to be more sensitive and accurate than manual interpretation. Sophisticated image processing hardware and software, especially produced for use with image data from NASA's LANDSAT satellite remote sensing instruments, will be used to develop and refine indices for objectively and efficiently measuring periodontal disease morbidity and activity. Geometric and radiometric features sensitive to the presence of periodontal disease will be extracted from digitized bitewing radiographic images of dry skulls, cadavers, and patients for use in evolving these indices. Image features that correlate with periodontal disease activity will be extracted in a semi-automated fashion under the supervision of an expert observer. Statistical pattern recognition methodology will be used to identify and describe periodontal disease activity based on these features. Manual measurements of alveolar bone loss will be used for validation of a computer-based morbidity index. For skulls and cadavers, consensus opinion of trained observers will be used for the validation of a computerized activity index, and for patients, validation will be based on longitudinal series of standardized radiographs. The usefulness of the morbidity and activity indices for predicting alveolar bone loss will be tested, and it will be determined whether improving and deteriorating periodontal health are associated with changes in radiometric features of digitized dental images.